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  • Open Access

    ARTICLE

    IOT Based Smart Parking System Using Ensemble Learning

    Walaa H. Elashmawi1,3, Ahmad Akram2, Mohammed Yasser2, Menna Hisham2, Manar Mohammed2, Noha Ihab2, Ahmed Ali4,5,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3637-3656, 2023, DOI:10.32604/iasc.2023.035605 - 15 March 2023

    Abstract Parking space is usually very limited in major cities, especially Cairo, leading to traffic congestion, air pollution, and driver frustration. Existing car parking systems tend to tackle parking issues in a non-digitized manner. These systems require the drivers to search for an empty parking space with no guarantee of finding any wasting time, resources, and causing unnecessary congestion. To address these issues, this paper proposes a digitized parking system with a proof-of-concept implementation that combines multiple technological concepts into one solution with the advantages of using IoT for real-time tracking of parking availability. User authentication More >

  • Open Access

    ARTICLE

    Early COVID-19 Symptoms Identification Using Hybrid Unsupervised Machine Learning Techniques

    Omer Ali1,2, Mohamad Khairi Ishak1,*, Muhammad Kamran Liaquat Bhatti2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 747-766, 2021, DOI:10.32604/cmc.2021.018098 - 04 June 2021

    Abstract The COVID-19 virus exhibits pneumonia-like symptoms, including fever, cough, and shortness of breath, and may be fatal. Many COVID-19 contraction experiments require comprehensive clinical procedures at medical facilities. Clinical studies help to make a correct diagnosis of COVID-19, where the disease has already spread to the organs in most cases. Prompt and early diagnosis is indispensable for providing patients with the possibility of early clinical diagnosis and slowing down the disease spread. Therefore, clinical investigations in patients with COVID-19 have revealed distinct patterns of breathing relative to other diseases such as flu and cold, which… More >

  • Open Access

    ARTICLE

    Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment

    Shumaila Shahzadi1, Fahad Ahmad1,*, Asma Basharat1, Madallah Alruwaili2, Saad Alanazi2, Mamoona Humayun2, Muhammad Rizwan1, Shahid Naseem3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2723-2749, 2021, DOI:10.32604/cmc.2021.014594 - 28 December 2020

    Abstract With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to… More >

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